At NVIDIA, we make a positive impact in the world through our inventions, the people who put them to use, and a culture that keeps them coming.

Our contributions were brought to life at the latest GPU Technology Conference, our annual developer conference. It focused on deep learning, a promising field of artificial intelligence that uses the massive amounts of data unleashed by the internet to teach computers to make predictions and perform seemingly magical tasks. Recent improvements in algorithms and NVIDIA GPUs capable of processing this torrent of data has enabled computers to recognize images, text and speech on their own — in some cases better than humans.

GPU-powered deep learning is already at the heart of many applications that amaze and delight us every day. It’s nothing short of miraculous that you can ask your phone a question and instantly get an answer — even more so when the answer is aware of your context and preferences. For most of us, it is wonderfully convenient. But for the blind and visually impaired, it provides a profound sense of freedom and self-reliance beyond what words can describe.

Deep learning is also sweeping through medical research. Researchers at IDSIA, a Swiss non-profit research institution focused on artificial intelligence, are using NVIDIA GPUs to train a neural network to determine the severity of breast cancer by detecting the growth rate of cancerous cells. The network is able to match the accuracy of highly trained doctors. At Austria’s Johannes Kepler University, researchers are using GPU-powered deep learning to determine the toxicity of new drugs, work that can accelerate the discovery of new treatments. And at the University of Toronto, scientists are attacking genetic diseases, such as autism, by applying deep neural networks to advance the study of the human genome.

The impact of our work in deep learning is proving to be broad and deep. IBM, Microsoft and Facebook are deploying GPU-powered deep learning across a variety of applications. Start-ups are doing so every day. And automakers are turning to deep learning to address their grand challenge — the self-driving car.

Adapting to the infinite nuances of driving down the road is second nature to us. For a computer operating on data from its camera, sonar and radar sensors, understanding the world is an unimaginably daunting task. There are too many possibilities to reasonably write software programs to respond to each of them. We built NVIDIA DRIVE PX, a self-driving car computer, which uses the power of our supercomputing GPUs and breakthroughs in artificial intelligence to learn the behavior of driving.

Such a car would know to behave differently when an oncoming vehicle is a school bus or an ambulance, if the door of a parked car on the side of the road opens suddenly, or if a ball rolls into the middle of the street. The fully autonomous car is years away. But benefits will appear shortly. As we work our way there, GPU-powered deep learning will deliver many features that will improve the safety of our roads.

I believe deep learning will be one of the most important breakthroughs since the internet. It is gratifying to see our work benefiting so many around the world. I can hardly wait to see what amazing creations will be made possible by what we’ve invented today.

I’m extremely proud of the culture we’ve built — one that can take on the most important challenges of our time. It’s efficient and agile. But, more importantly, it’s a culture inspired by the world’s toughest problems. Over the years, the work of our people has built and shaped major industries — from gaming, to product design, to film, to medical research, to cloud computing. People know they can come to NVIDIA to do their life’s work. That culture not only ensures the health of our company. It helps us make a bigger contribution to society.